Classification method and system for grid-connected working conditions of energy storage system, storage medium and server

A technology of an energy storage system and a classification method, which is applied to storage media and servers, a classification method for grid-connected working conditions of an energy storage system, and the system field, can solve problems such as difficulty in guaranteeing accuracy and complex and changeable grid-connected working conditions.

Pending Publication Date: 2022-05-27
CHINA ELECTRIC POWER RES INST +1
View PDF2 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] To sum up, although these related studies have made some progress in the management of energy storage operating conditions such as classification and identification, the grid-connected operating conditions are complex and changeable. It is difficult to guarantee the accuracy of individual scene identification and classification management when the power station participates in peak shaving, frequency regulation and other application scenarios

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Classification method and system for grid-connected working conditions of energy storage system, storage medium and server
  • Classification method and system for grid-connected working conditions of energy storage system, storage medium and server
  • Classification method and system for grid-connected working conditions of energy storage system, storage medium and server

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0057] see figure 1 , a method for classifying grid-connected working conditions of an energy storage system according to an embodiment of the present invention includes the following steps:

[0058] S1. Collect the data of the grid-connected operation condition of the energy storage power station;

[0059] S2. Obtain the data set to be classified by preprocessing the data of the grid-connected operation condition of the energy storage power station;

[0060] S3. Input the data set to be classified into the pre-built random forest classification model to determine whether it is necessary to analyze the influence of characteristic parameters. If not, the random forest classification model directly outputs the classification results of the grid-connected conditions of the energy storage system; if necessary , firstly calculate the VIM of the feature parameter importance of the working condition, complete the training of the random forest classification model, and then use the t...

Embodiment 2

[0079] The implementation and effect of the method for classifying the grid-connected working conditions of the energy storage system of the present invention will be described below through practical cases.

[0080] In this example, a total of N=238 groups of data on C=5 actual operating conditions of grid-connected lithium-ion battery energy storage power stations above MW level are collected, 16 groups of auxiliary frequency modulation on the power supply side, 27 groups of combined photovoltaic and storage, wind-storage smoothing and The planned output is 96 and 73 groups, and 26 groups of grid-side peak shaving and valley filling. The energy storage systems of the above five applications operate at a power of 0.1 to 1P 0 , The capacity is 5-80% DOD and the time is in the range of seconds to hours, starting from the magnitude, response speed, working time, waveform characteristics, etc. , select M=20 performance characterization parameter sets X that are closely related t...

Embodiment 3

[0092] The embodiment of the present invention also proposes a classification system for grid-connected working conditions of an energy storage system, including:

[0093] The data acquisition module 1 is used to collect the data of the grid-connected operation condition of the energy storage power station;

[0094] The to-be-classified data set acquisition module 2 is used to obtain the to-be-classified data set by preprocessing the grid-connected operating condition data of the energy storage power station;

[0095] The random forest classification module 3 is used to input the data set to be classified into the pre-built random forest classification model to determine whether it is necessary to analyze the influence of characteristic parameters. If not, the random forest classification model directly outputs the grid connection conditions of the energy storage system If necessary, first calculate the VIM of the feature parameters of the operating conditions, complete the tr...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention discloses a classification method and system for grid-connected working conditions of an energy storage system, a storage medium and a server. The method comprises the steps of collecting grid-connected operation working condition data of an energy storage power station; the method comprises the following steps: preprocessing grid-connected operation condition data of an energy storage power station to obtain a to-be-classified data set; inputting the to-be-classified data set into a pre-constructed random forest classification model, judging whether the influence of the characteristic parameters needs to be analyzed or not, and if not, directly outputting a classification result of the grid-connected working condition of the energy storage system by the random forest classification model; and if necessary, firstly calculating the importance measurement VIM of the characteristic parameters of the working condition, completing the training of the random forest classification model, and then outputting the classification result of the grid-connected working condition of the energy storage system by using the trained random forest classification model. The method has high tolerance to abnormal values and noise of working condition operation data, can perform quick, accurate and unbiased estimation classification management on a large amount of actual operation working condition data of the energy storage power station, and meanwhile quantitatively manages the importance of working condition characterization parameters.

Description

technical field [0001] The invention belongs to the technical field of electrochemical energy storage, and in particular relates to a classification method, system, storage medium and server for grid-connected working conditions of an energy storage system. Background technique [0002] With the rapid rise of the global energy Internet, the increase in the proportion of distributed power sources and the increase in the number of loads such as electric vehicles have put forward higher requirements for the flexible adjustment capability of the power system, and the new energy storage system represented by electrochemical energy storage It has the characteristics of flexible configuration and high dispatchability, and has been quickly applied on the power supply side, grid side and user side of the power system. [0003] The diversity of electrochemical energy storage application scenarios makes the application conditions carried by electrochemical energy storage different, and...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Applications(China)
IPC IPC(8): G06K9/62G06Q10/06G06Q50/06
CPCG06Q10/0639G06Q50/06G06F18/211G06F18/24323G06F18/214Y04S10/50
Inventor 谷毅王雅丽张甲雷梁昊陈继忠闫涛杨水丽王凯丰李相俊张明霞
Owner CHINA ELECTRIC POWER RES INST
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products